Search: “tools”

arXiv:2605.25271v1 Announce Type: cross Abstract: We study the symmetric polynomial prod_{alphain A_{n,d}}igl(1+alpha_1 x_1+dots+alpha_n x_nigr) where A_{n,d}:={alphainZ_{ge 0}^n:|alpha|=d}, which is

arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov

arXiv:2410.10652v4 Announce Type: replace-cross Abstract: Cells in multicellular organisms coordinate to form structural and functional niches. With spatial transcriptomics (ST) enabling gene expressi

arXiv:2605.25480v1 Announce Type: new Abstract: LLM agents require retrieval to behave less like one-shot context fetching and more like reasoning: searching, reading, traversing, and deciding when ev

arXiv:2605.24899v1 Announce Type: new Abstract: Ontologies represent the conceptual knowledge of a domain. At the core of an ontology is the taxonomy of concepts and subconcepts that represent specifi

arXiv:2510.12787v4 Announce Type: replace Abstract: We present Ax-Prover, a multi-agent system for automated theorem proving in Lean that can solve problems across diverse scientific domains and opera

arXiv:2605.23262v1 Announce Type: new Abstract: The development of LLM agents has led to a growing body of work on knowledge-work AI, including coding, research, and healthcare. However, current knowl

arXiv:2605.23653v1 Announce Type: new Abstract: Timely and transparent feedback is essential for effective surgical training, yet current assessment remains dependent on expert observation, limiting s

arXiv:2605.22874v1 Announce Type: new Abstract: Effectively translating between natural language (NL) and formal logics like Linear Temporal Logic (LTL) requires expertise that limits formal verificat

arXiv:2512.11587v2 Announce Type: replace Abstract: Even for the gradient descent (GD) method applied to neural network training, understanding its optimization dynamics, including convergence rate, i

arXiv:2603.04383v2 Announce Type: replace-cross Abstract: YouTube has evolved into a powerful platform where creators monetize their influence through affiliate marketing, raising concerns about trans

arXiv:2605.21496v1 Announce Type: cross Abstract: Frontier language models are being deployed into clinical workflows faster than the infrastructure to evaluate them safely. Static medical-QA benchmar

arXiv:2605.20704v1 Announce Type: cross Abstract: Autonomous AI agents that spawn sub-agent swarms create a safety gap: existing credential revocation mechanisms, OAuth~2.0 introspection, OCSP, and W3

arXiv:2605.21453v1 Announce Type: cross Abstract: As AI agents increasingly contribute to code development and maintenance, there is still limited empirical evidence on the quality and risk characteri

arXiv:2605.21026v1 Announce Type: new Abstract: To accelerate automated remanufacturing, robotic disassembly must be considered during the product design phase. However, designers currently lack quant

arXiv:2512.03671v2 Announce Type: replace Abstract: The rise of generative AI (GenAI) chatbots accessible via conversational interfaces is transforming digital interactions and holds economic promise.

arXiv:2605.20833v1 Announce Type: new Abstract: Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of person

arXiv:2605.20932v1 Announce Type: new Abstract: Wheeled-legged robots, which have wheels at their feet and achieve high mobility by coordinating wheel drive and leg drive, have been developed. These r

arXiv:2605.18770v1 Announce Type: cross Abstract: We present a collaborative agentic GraphRAG framework for expert analysis of commercial registry data. Public registries are often formally accessible

arXiv:2510.25064v2 Announce Type: replace Abstract: Estimating the cognitive complexity of reading comprehension (RC) items is crucial for assessing item difficulty before it is administered to learne

arXiv:2605.19926v1 Announce Type: new Abstract: The progression of reinforcement learning algorithms have been driven by challenging benchmarks. The rate in which a researcher can iterate on a problem

arXiv:2605.19717v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate Computer-Aided Design (CAD), yet lack physical comprehension required for reliable engineering design. Instead

arXiv:2605.18878v1 Announce Type: cross Abstract: Hospital readmission within 30 days of discharge is a leading driver of morbidity, mortality, and avoidable healthcare expenditure in congestive heart

arXiv:2605.19338v1 Announce Type: cross Abstract: Frontier AI models and multi-agent systems have led to significant improvements in mathematical reasoning. However, for problems requiring extended, l

arXiv:2605.19410v1 Announce Type: new Abstract: Segmentation has become easy when the concept is known, requiring retrieval of a learned visual grounding from text. It remains hard for open ad-hoc con

arXiv:2509.19182v2 Announce Type: replace-cross Abstract: Incorporating natural language input has the potential to improve the capabilities of biomedical data discovery interfaces. However, user inte

arXiv:2605.18661v1 Announce Type: new Abstract: AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents c

arXiv:2605.17352v1 Announce Type: new Abstract: Despite substantial advances in large language models (LLMs), generating factually consistent responses for knowledge-intensive question answering remai

arXiv:2605.16679v1 Announce Type: cross Abstract: End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions

arXiv:2605.16441v1 Announce Type: cross Abstract: Beat-level Electrocardiography (ECG) arrhythmia detection aims to assign an arrhythmia class to each beat in a recording, yet many existing systems tr

arXiv:2605.16336v1 Announce Type: cross Abstract: Large language models (LLMs) have made fluent essay writing, code drafting, and quiz answering instantly available to students at every level, from se

arXiv:2605.16292v1 Announce Type: cross Abstract: Perceptions of intelligence shape how learners evaluate and rely on artificial intelligence (AI) systems. Despite rapid advances in AI capabilities, t

arXiv:2605.16821v1 Announce Type: new Abstract: The rapid evolution of Large Language Model (LLM) agents has produced diverse interaction paradigms, yet few production systems integrate multiple parad

arXiv:2605.17172v1 Announce Type: cross Abstract: Personal AI stacks, like OpenClaw and Hermes Agent, are becoming central to daily work, yet they route nearly every query (often over sensitive local

arXiv:2605.17548v1 Announce Type: cross Abstract: Code review has evolved for decades, from informal peer checking to today's pull request (PR) workflows, yet it remains a largely manual, uneven, and

arXiv:2501.01046v4 Announce Type: replace Abstract: Dataset deduplication is widely recognized as a crucial preprocessing step that enhances data quality and improves the performance of large language

arXiv:2605.17946v1 Announce Type: new Abstract: Multimodal large language models are increasingly used as agent backbones that understand multimodal inputs, plan retrieval actions, invoke external too

arXiv:2605.17170v1 Announce Type: new Abstract: Agentic workloads have emerged as a major workload for LLM inference. They differ significantly from chat-only workloads, requiring long-context process

arXiv:2605.16699v1 Announce Type: new Abstract: Capped-usage SaaS products -- LLM subscriptions such as Claude Code and ChatGPT, cloud platforms such as Vercel and Cloudflare Workers, corporate benefi

arXiv:2605.16205v1 Announce Type: new Abstract: Deploying compound LLM agents in adversarial, partially observable sequential environments requires navigating several design dimensions: (1) what the a

arXiv:2605.15306v1 Announce Type: new Abstract: Data augmentation is widely recognized for improving generalization in deep networks, yet its impact on the geometry of learned representations remains

arXiv:2509.21465v3 Announce Type: replace Abstract: Tabular foundation models are becoming increasingly popular for low-resource tabular problems. These models make up for small training datasets by p

arXiv:2602.14674v4 Announce Type: replace Abstract: Gradual argumentation is a field of symbolic AI which is attracting attention for its ability to support transparent and contestable AI systems. It

arXiv:2605.14980v1 Announce Type: cross Abstract: Analyzing microscopy images to extract biological object properties (e.g., their morphological organization, temporal dynamics, and population density

arXiv:2603.29665v2 Announce Type: replace Abstract: Agentic systems for business process automation often require compliance with policies governing conditional updates to the system state. Evaluation

arXiv:2601.19924v2 Announce Type: replace-cross Abstract: We investigate the capabilities and scalability of Large Language Models (LLMs) in optimization modeling, a domain requiring structured reason